Effect of extended heat stress in dairy cows on productive and behavioral traits.

This study evaluates the response of dairy cows to short and extended heat stressing conditions (from 1 to 28 days), as expressed in changes in their behavior. Due to climate change, heat stress and strong heat waves are frequently affecting the productivity and behavior of dairy cows. In the five years under study from 2018 to 2022, two were characterized by extremely strong heat waves occurring in the region analyzed in this study (Northern Italy). The dairy cattle farm involved in this study is located in Northern Italy and includes about 1 600 Holstein Friesian lactating dairy cows. Phenotypic data were provided by the Afimilk system and compromised behavioral and productive traits. Behavioral traits analyzed were activity, rest time, rest bouts, rest ratio, rest per bout and restlessness. Production traits were daily milk yield, average milking time, somatic cell count, fat percentage, protein percentage and lactose percentage. Climate data came from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources database. Heat stress was analyzed considering Temperature-Humidity Index (THI) averaged over 28 different time windows of continuous heat stress. Results showed that rest time and milk yield were the two traits most affected by the increased THI. Rest time was immediately affected by high THI, showing a marked decrease already from 1d window and maintaining this all over the other windows. Furthermore, results show that rest time and rest ratio were only slightly negatively correlated with milk yield (-0.14 and -0.15). In addition, heat stress has a different effect depending on parity and lactation stages on the studied traits. In conclusion, the results indicate that heat stress increases activity and compromises milk production, rest time and milk quality traits. Results further suggest that rest time can be a better parameter than activity to describe the effects of heat stress on dairy cattle. The novel approach used in this study is based on the use of different time windows (up to 28 days) before the emergence of undesired THI and allows to identify the traits that are immediately influenced by the undesirable THI values and those that are influenced only after a prolonged heat stress period.

Effects of cow reproductive status, parity and lactation stage on behaviour and heavy breathing indications of a commercial accelerometer during hot weather conditions.

Heat stress presents one of the most urgent challenges to modern dairy farming, having major detrimental impacts on cow welfare, health, and production. Understanding the effect of cow factors (reproductive status, parity, and lactation stage) on the physiological and behavioural response to hot weather conditions is essential for the accurate detection and practical application of heat mitigation strategies. To study this, collars with commercial accelerometer-based sensors were fitted on 48 lactation dairy cows to record behaviour and heavy breathing from late spring to late summer. The temperature-humidity index (THI) was calculated from measurements of 8 barn sensors. We found that, above a THI of 84, cows in advanced pregnancy (>90 days) spent more time breathing heavily and less time eating and in low activity than other cows, while cows in early pregnancy (≤90 days) spent less time breathing heavily, more time eating and in low activity. Cows with 3+ lactations showed less time breathing heavily and in high activity and more time ruminating and in low activity than cows with fewer lactations. Although lactation stage interacted significantly with THI on time spent breathing heavily, ruminating, eating, and in low activity, there was no clear indication at which lactation stage cows were more sensitive to heat. These findings show that cow factors affect the cow's physiological and behavioural response to heat, which could be used to provide group-specific heat abatement strategies, thereby improving heat stress management.

Climate change and socio-economic assessment of PLF in dairy farms: Three case studies.

Precision Livestock Farming (PLF) techniques include sensors and tools to install on livestock farms and/or animals to monitor them and support the decision making process of farmers, finally early detecting alerting conditions and improving the livestock efficiency. Direct consequences of this monitoring include enhanced animal welfare, health and productivity, improved farmer lifestyle, knowledge, and traceability of livestock products. The indirect consequences, instead, include improved Carbon Footprint and socio-economic indicators of livestock products. In this context, the aim of this paper is to develop an indicator applicable to dairy cattle farming that takes into account concurrently these indirect consequences. The indicator was developed combining the three sustainability pillars (with specific criteria): environmental (carbon footprint), social (5 freedoms of animal welfare and antimicrobial use) and economic (cost of technology and manpower use). The indicator was then tested on 3 dairy cattle farms located in Italy, where a baseline traditional scenario (BS) was compared with an alternative scenario (AS) where PLF techniques and improved management solutions were adopted. The results highlighted that the carbon footprint reduced in all AS by 6-9 %, and the socio-economic indicators entailed improvements in animals and workers welfare with some differences based on the tested technique. Investing in PLF techniques determines positive effects on all/almost all the criteria adopted for the sustainability indicator, with case-specific aspects to consider. Being a user-friendly tool that supports the testing of different scenarios, this indicator could be used by stakeholders (policy makers and farmers in particular) to identify the best direction towards investments and incentive policies.

The Potentialities of Machine Learning for Cow-Specific Milking: Automatically Setting Variables in Milking Machines.

In dairy farming, milking-related operations are time-consuming and expensive, but are also directly linked to the farm's economic profit. Therefore, reducing the duration of milking operations without harming the cows is paramount. This study aimed to test the variation in different parameters of milking operations on non-automatic milking machines to evaluate their effect on a herd and finally reduce the milking time. Two trials were set up on a dairy farm in Northern Italy to explore the influence of the pulsation ratio (60:40 vs. 65:35 pulsation ratio) and that of the detachment flow rate (600 g/min vs. 800 g/min) on milking performance, somatic cell counts, clinical mastitis, and teats score. Moreover, the innovative aspect of this study relates to the development of an optimized least-squares support vector machine (LSSVM) classification model based on the sparrow search algorithm (SSA) to predict the proper pulsation ratio and detachment flow rate for individual cows within the first two minutes of milking. The accuracy and precision of this model were 92% and 97% for shortening milking time at different pulsation ratios, and 78% and 79% for different detachment rates. The implementation of this algorithm in non-automatic milking machines could make milking operations cow-specific.

Development of a New Wearable 3D Sensor Node and Innovative Open Classification System for Dairy Cows' Behavior.

Monitoring dairy cattle behavior can improve the detection of health and welfare issues for early interventions. Often commercial sensors do not provide researchers with sufficient raw and open data; therefore, the aim of this study was to develop an open and customizable system to classify cattle behaviors. A 3D accelerometer device and host-board (i.e., sensor node) were embedded in a case and fixed on a dairy cow collar. It was developed to work in two modes: (1) acquisition mode, where a mobile application supported the raw data collection during observations; and (2) operating mode, where data was processed and sent to a gateway and on the cloud. Accelerations were sampled at 25 Hz and behaviors were classified in 10-min windows. Several algorithms were trained with the 108 h of behavioral data acquired from 32 cows on 3 farms, and after evaluating their computational/memory complexity and accuracy, the Decision Tree algorithm was selected. This model detected standing, lying, eating, and ruminating with an average accuracy of 85.12%. The open nature of this system enables for the addition of other functions (e.g., real-time localization of cows) and the integration with other information sources, e.g., microenvironment and air quality sensors, thereby enhancing data processing potential.

Life cycle assessment of Parmigiano Reggiano PDO cheese with product environmental footprint method: A case study implementing improved slurry management strategies.

The environmental impact of Parmigiano Reggiano PDO cheese was quantified using the Product Environmental Footprint Category Rules (PEFCRs) in a Traditional System (TS) and in an Improved Management System (IMS). The TS differs from IMS with respect to slurry management (raw slurry storage vs anaerobic digestion and storage of the liquid fraction of digestate) and application of nutrients to the field (by slurry tanker with a diverter plate vs soil injection at pre-sowing and side dressing). Two additional scenarios were evaluated by considering the possible environmental enhancement achievable by reducing enteric methane production and by using soybean grain produced in Italy as the protein source for animals' diets. The environmental impact was quantified both for 1 kg of fat and protein corrected milk (FPCM) and for the production of 10 g dry matter equivalent of cheese as single score. For the first assessment, the environmental impact results were 124 and 112 µPt kg FPCM-1 for TS and IMS, respectively. In the second case, it was 10.8 µPt and 9.9 µPt 10 g dry matter equivalent-1 of cheese, for TS and IMS, respectively. The specific cost for reducing the GHG emissions in this production chain was equal to 34 € Mg-1 milk produced. Finally, although specific studies should consider the reduction of enteric methane emissions and the use of soybean grain nationally produced as feed source, the scenarios evaluated in this study highlighted some potential for environmental improvements. Even small environmental improvements to the Parmigiano Reggiano PDO cheese supply chain can bring substantial improvements to the sustainability of the food market, because of the widespread demand on the global market of Parmigiano Reggiano and of its chance of attracting consumers who are sensitive to environmental problems.

Dairy Cow Behavior Is Affected by Period, Time of Day and Housing.

Dairy cow behavior is affected by external and endogenous factors, including time of year, barn microclimate, time of day and housing. However, little is known about the combined effects of these factors. Data were collected on eight farms in Northern Italy during summer, winter and a temperate season. The temperature-humidity index (THI) was recorded using environmental sensors, whereas cow behavior was monitored using leg accelerometers and cameras. Period, time of day and their interaction all significantly affected lying, standing and feeding behavior. However, although THI had a significant negative effect on lying and a positive effect on standing during daytime (all p < 0.001), during nighttime, it only had a significant negative effect on lying duration and mean lying bout duration (p < 0.001 for both). There was also significant variation between farms in all behavioral parameters, as well as interactions with period and time of day. For instance, farm differences in lying duration were more pronounced during daytime than during nighttime. These findings show how housing can interact with other factors, such as period of the year and time of day, and illustrate the influence of barn structure and farm management on cow behavior and, consequently, their welfare.

Comparison of ammonia air concentration before and during the spread of COVID-19 in Lombardy (Italy) using ground-based and satellite data.

Several anthropogenic activities have undergone major changes following the spread of the COVID-19 pandemic, which in turn has had consequences on the environment. The effect on air pollution has been studied in detail in the literature, although some pollutants, such as ammonia (NH3), have received comparatively less attention to date. Focusing on the case of Lombardy in Northern Italy, this study aimed to evaluate changes in NH3 atmospheric concentration on a temporal scale (the years from 2013 to 2019 compared to 2020) and on a spatial scale (countryside, city, and mountain areas). For this purpose, ground-based (from public air quality control units scattered throughout the region) and satellite observations (from IASI sensors on board MetOp-A and MetOp-B) were collected and analyzed. For ground-based measurements, a marked spatial variability is observed between the different areas while, as regards the comparison between periods, statistically significant differences were observed only for the countryside areas (+31% in 2020 compared to previous years). The satellite data show similar patterns but do not present statistically significant differences neither between different areas, nor between the two periods. In general, there have been no reduction effects of atmospheric NH3 as a consequence of COVID-19. This calls into question the role of the agricultural sector, which is known to be the largest responsible for NH3 emissions. Even if the direct comparison between the two datasets shows little correlation, their contextual consideration allows making more robust considerations regarding air pollutants.

Relating Lying Behavior With Climate, Body Condition Score, and Milk Production in Dairy Cows.

Attention on animal behavior and welfare has been increasing. Scientific knowledge about the effect of behavior and welfare on animals' production augmented and made clear the need of improving their living conditions. Among the variables to monitor in dairy cattle farming, lying time represents a signal for health and welfare status as well as for milk production. The aim of this study is to identify the relationship among the lying behavior of dairy cows and milk production, body condition score (BCS), weather variables, and the temperature-humidity index (THI) in the barn from a dairy farm located in Northern Italy. One-year data were collected on this farm with sensors that allowed monitoring of the environmental conditions in the barn and the activity of primiparous lactating cows. Principal components analysis (PCA), factor analysis (FA), generalized linear model select (GLMSelect), and logistic analysis (LA) were carried out to get the relationships among variables. Among the main results, it emerges that the effect of weather parameters is quite restrained, except for THI > 70, which negatively affects the lying time. In addition, the most productive cows are found to lie down more than the less productive ones, and the parameters of milk production, lying time, and BCS are found to be linked by a similar trend.

Describing the trend of ammonia, particulate matter and nitrogen oxides: The role of livestock activities in northern Italy during Covid-19 quarantine.

Nitrogen oxides (NOx), sulphur oxides (SOx) and ammonia (NH3) are among the main contributors to the formation of secondary particulate matter (PM2.5), which represent a severe risk to human health. Even if important improvements have been achieved worldwide, traffic, industrial activities, and the energy sector are mostly responsible for NOx and SOx release; instead, the agricultural sector is mainly responsible for NH3 emissions. Due to the emergency of coronavirus disease, in Italy schools and universities have been locked down from late February 2020, followed in March by almost all production and industrial activities as well as road transport, except for the agricultural ones. This study aims to analyze NH3, PM2.5 and NOx emissions in principal livestock provinces in the Lombardy region (Brescia, Cremona, Lodi, and Mantua) to evaluate if and how air emissions have changed during this quarantine period respect to 2016-2019. For each province, meteorological and air quality data were collected from the database of the Regional Agency for the Protection of the Environment, considering both data stations located in the city and the countryside. In the 2020 selected period, PM2.5 reduction was higher compared to the previous years, especially in February and March. Respect to February, PM2.5 released in March in the city stations reduced by 19%-32% in 2016-2019 and by 21%-41% in 2020. Similarly, NOx data of 2020 were lower than in the 2016-2019 period (reduction in March respect to February of 22-42% for 2016-2019 and of 43-62% for 2020); in particular, this can be observed in city stations, because of the current reduction in anthropogenic emissions related to traffic and industrial activities. A different trend with no reductions was observed for NH3 emissions, as agricultural activities have not stopped during the lockdown. Air quality is affected by many variables, for which making conclusions requires a holistic perspective. Therefore, all sectors must play a role to contribute to the reduction of harmful pollutants.

A Survey of Dairy Cattle Behavior in Different Barns in Northern Italy.

Due to its increasing pressure on dairy cows, studies that investigate how to cope with heat stress are needed. The heat stress affects multiple aspects of cows' lives, among which their behavior and welfare. In this study, a survey was carried out in eight farms located in Northern Italy to monitor and evaluate the environmental aspects of the barns and the behavioral responses of dairy cows. For one year, three periods were monitored: thermoneutral (T_S), hot (H_S) and cold (C_S) seasons. Temperature and relative humidity were measured by environmental sensors, and lying vs. standing time, number of lying bouts and their average duration were collected by accelerometers. The temperature-humidity index (THI) was quantified inside and outside of the barn. Results show that at the increase of the THI, behavioral adaptations occurred in all the farms, especially with a reduction of lying time and an increase of respiration rate. Four of the eight farms need interventions for improving the cows' welfare. Here, environmental problems should be solved by introducing or improving the efficacy of the forced ventilation or by modifying the barn structure. Monitoring dairy barns with sensors and Precision Livestock Farming techniques can be helpful for future livestock farming to alert farmers on the need for their interventions to respond immediately to unwanted barn living conditions.

Barley production in Spain and Italy: Environmental comparison between different cultivation practices.

In Europe, around 12 million ha are cultivated with barley and Spain and Italy are two important producers' countries. This study aims to compare the cultivation of barley of two different contexts, Spain and Italy, evaluating the related environmental performances; this is carried out considering the similar latitude and climatic conditions of the two countries, but taking into account the different average mechanisation solutions that differentiate considerably the two production frameworks. Inventory data about barley cultivation were gathered mainly by questionnaires with farmers and technical expert interviews. To quantify the environmental performances of barley production in the two Countries, the Life Cycle Assessment approach was applied and 1 ton of grain at the commercial moisture was selected as reference unit and 12 impact categories were evaluated. The outcomes of the impact assessment highlight how for 7 of the 12 evaluated impact categories, barley production in Spain shows a higher impact respect to the Italian production (from +7% for photochemical oxidant formation to +120% for freshwater ecotoxicity) mainly due to the lower grain yield and to the higher consumption of mineral fertilisers. For the other evaluated environmental effects, the Spanish production performs better than the Italian one, mostly because of the lower emissions of ammonia into the air. Yield is the main driver of the environmental effects. Additionally, due to mechanisation of field operations and to fertilisations, wide differences on the environmental side emerge from the comparison. There is a trade-off between the Spanish production, where the use of mineral fertilisers reduces all the environmental effects related to ammonia volatilisation, and the Italian barley cultivation, where the use of animal slurry improves the results on the impact categories affected by the fertiliser production but worsens those affected by the nitrogen emissions.

Bioconversion of fruit and vegetable waste into earthworms as a new protein source: The environmental impact of earthworm meal production.

Food waste is recognized as a global issue affecting the sustainability of the food supply chain. The unnecessary exploitation of natural resources (land, water and fossil energy) and production of greenhouse gas emissions (GHG) make the reduction of food waste a key point. In this context, the use of fruit and vegetable waste (FVW) as growth substrate for fresh earthworms to produce dried meal for feed and food purpose can be recognized as a viable solution. Therefore, the aim of this study is to evaluate the environmental impact of the bioconversion of FVW into earthworm meal to be used as new food/feed source. This is carried out by adopting the Life Cycle Assessment (LCA) method with an attributional approach and solving the multifunctionality of the system with an economic allocation between earthworms and vermicompost. The results show that the main process hotspots are the emissions of methane, dinitrogen monoxide and ammonia taking place during vermicomposting, as well as FVW transport and electricity consumed during fresh earthworm processing. Respect to the one used as feed, the dried meal with food purpose shows a higher impact due to the higher economic value and to the higher electricity consumed during freeze drying compared to the oven-drying process for feed meal production. Enhancing productivity and reducing energy consumption are necessary to improve the sustainability of earthworm meal as food/feed source.

Environmental impact of strawberry production in Italy and Switzerland with different cultivation practices.

In this study, the environmental impact of strawberry production in Italy and Switzerland was evaluated using the Life Cycle Assessment (LCA) approach. The main differences between the two countries are the cultivation practices: crop cycle duration (1 year in Switzerland and 2 or 3 years in Italy), soil management and cultivation in open and protected fields. For all the environmental impact categories evaluated with LCA, strawberry production in Switzerland shows higher impacts respect to the Italian production. The impact reduction related to the Italian production in open fields without soil sterilisation ranges from 96% (for photochemical oxidant formation) to 35% (for freshwater eutrophication). For Swiss production, soil sterilisation is by far the main environmental hotspot for all the evaluated environmental effects except for toxicity-related impact categories and for resources consumption (i.e. manufacturing, maintenance and disposal of tunnel). Conversely, the main hotspot in Italy differs depending on the considered categories. Moreover, the 3-years cycle duration has a higher impact respect to the 2-years one because of the low yield in the third year that worsens the outcomes. Finally, sensitivity and uncertainty analysis were performed. The environmental results are deeply affected by yield variation and only slightly by changes in the life span of the tunnels while the uncertainty related to the selection of the data source, the model imprecision, and the variability of data does not affect significantly the results, except for the toxicity-related impact categories.

Delving the environmental impact of roundwood production from poplar plantations.

The environmental impact of timber production from poplar plantation was evaluated by means of Life Cycle Assessment (LCA) using an attributional approach. A comparison was performed between a baseline scenario and an alternative one in which different harvesting operations were identified. An economic allocation was adopted to solve the multi-functionality of the studied process, by taking into account the price of the main product and of co-products. Sensitivity analysis was performed on alternative mass allocation and yield variations that derive from using high sustainability plants or from climate stress. A different characterization method was also analyzed. Among the different field operations, crop management involves a higher impact respect to field preparation-planting and harvesting-soil restoring. Emissions related to fertilizers' applications are the main responsible for acidification, eutrophications and particular matter formation. The results show that the modelling of the environmental impact of timber production is robust. The alternative scenario resulted better than baseline for all impact categories (impact reduction ranging from 0.1% to 12.4%), except for HT-noc (+12.2%) and POF (+20.6%), due to fuel and oil consumption in the chainsaw used for harvesting. In the next years, introducing high-sustainability clones (characterized by higher yield and higher resistance to pests and drought) could be an effective way for reducing the environmental impact of poplar roundwood production.

Environmental impact assessment of alfalfa (Medicago sativa L.) hay production.

On-farm production of hay and high-protein-content feed has several advantages such as diversification of on-farm cultivated crops, reduction of off-farm feed concentrates transported over long distances and a reduction in runoff during the winter season if grown crops are perennial. Among those crops cultivated for high-protein-content feed, alfalfa (Medicago sativa L.) is one of the most important in the Italian context. Nevertheless, up to now, only a few studies have assessed the environmental performance of alfalfa hay production. In this study, using the Life Cycle Assessment approach, the environmental impact of alfalfa hay production in Northern Italy was analyzed. More in detail, two production practices (without and with irrigation) were compared. The results show that alfalfa hay production in irrigated fields has a better environmental performance compared to non-irrigated production, mainly because of the yield increase achieved with irrigation. In particular, for the Climate Change impact category, the impact is equal to 84.54 and 80.21kgCO2/t of hay for the scenario without and with irrigation, respectively. However, for two impact categories (Ozone Depletion and Human Toxicity-No Cancer Effect), the impact of irrigation completely offsets the yield increase, and the cultivation practice without irrigation shows the best environmental performance. For both scenarios, the mechanization of harvest is the main environmental hotspot, mostly due to fuel consumption and related combustion emissions. Wide differences were highlighted by comparing the two scenarios with the Ecoinvent process of alfalfa hay production; these differences are mostly due to the cultivation practice and, in particular, to the more intensive fertilization in Swiss production.

Water Footprint of crop productions: A review.

Water Footprint is an indicator recently developed with the goal of quantifying the virtual content of water in products and/or services. It can also be used to identify the worldwide virtual water trade. Water Footprint is composed of three parts (green, blue and grey waters) that make the assessment complete in accordance with the Water Footprint Network and with the recent ISO14046. The importance of Water Footprint is linked to the need of taking consciousness about water content in products and services and of the achievable changes in productions, diets and market trades. In this study, a literature review has been completed on Water Footprint of agricultural productions. In particular, the focus was paid on crops for the production of food and bioenergy. From the review, the development of the Water Footprint concept emerged: in early studies the main goal was to assess products' water trade on a global scale, while in the subsequent years, the goal was the rigorous quantification of the three components for specific crops and in specific geographical areas. In the most recent assessments, similarities about the methodology and the employed tools emerged. For 96 scientific articles on Water Footprint indicator of agricultural productions, this literature review reports the main results and analyses weaknesses and strengths. Seventy-eight percent of studies aimed to quantify Water Footprint, while the remaining 22% analysed methodology, uncertainty, future trends and comparisons with other footprints. It emerged that most studies that quantified Water Footprint concerned cereals (33%), among which maize and wheat were the most investigated crops. In 46% of studies all the three components were assessed, while in 18% no indication about the subdivision was given; in the remaining 37%, only blue or green and blue components were quantified.

Anaerobic digestion and milking frequency as mitigation strategies of the environmental burden in the milk production system.

The aim of the study was to assess, through a cradle to farm gate Life Cycle Assessment, different mitigation strategies of the potential environmental impacts of milk production at farm level. The environmental performances of a conventional intensive dairy farm in Northern Italy (baseline scenario) were compared with the results obtained: from the introduction of the third daily milking and from the adoption of anaerobic digestion (AD) of animal slurry in a consortium AD plant. The AD plant, fed only with animal slurries coming also from nearby farms. Key parameters concerning on-farm activities (forage production, energy consumptions, agricultural machines maintenance, manure and livestock management), off-farm activities (production of fertilizers, pesticides, bedding materials, purchased forages, purchased concentrate feed, replacement animals, agricultural machines manufacturing, electricity, fuel) and transportation were considered. The functional unit was 1kg fat and protein corrected milk (FPCM) leaving the farm gate. The selected environmental impact categories were: global warming potential, acidification, eutrophication, photochemical oxidation and non-renewable energy use. The production of 1kg of FPCM caused, in the baseline scenario, the following environmental impact potentials: global warming potential 1.12kg CO2 eq; acidification 15.5g SO2 eq; eutrophication 5.62g PO4(3-) eq; photochemical oxidation 0.87g C2H4 eq/kg FPCM; energy use 4.66MJeq. The increase of milking frequency improved environmental performances for all impact categories in comparison with the baseline scenario; in particular acidification and eutrophication potentials showed the largest reductions (-11 and -12%, respectively). In anaerobic digestion scenario, compared to the baseline one, most of the impact potentials were strongly reduced. In particular the most important advantages were in terms of acidification (-29%), global warming (-22%) and eutrophication potential (-18%). The AD of cow slurry is confirmed as an effective strategy to mitigate the environmental impact of milk production at farm level.

Assessment of the influence of energy density and feedstock transport distance on the environmental performance of methane from maize silages.

In Europe, thanks to public subsidy, the production of electricity from anaerobic digestion (AD) of agricultural feedstock has considerably grown and several AD plants were built. When AD plants are concentrated in specific areas (e.g., Northern Italy), increases of feedstock' prices and transport distances can be observed. In this context, as regards low-energy density feedstock, the present research was designed to estimate the influence of the related long-distance transport on the environmental performances of the biogas-to-electricity process. For this purpose the following transport systems were considered: farm trailers and trucks. For small distances (<5 km), the whole plant silage shows the lowest impact; however, when distances increase, silages with higher energy density (even though characterised by lower methane production per hectare) become more environmentally sustainable. The transport by trucks achieves better environmental performances especially for distances greater than 25 km.